Self-organizing fuzzy controller based on fuzzy neural network

被引：1

作者：

Cho, Seongwon ^{[1
]}

Kim, Jaemin ^{[1
]}

Chung, Sun-Tae ^{[2
]}

机构：

[1] Hongik Univ, Sch Elect & Elect Engn, 72-1 Sangsu Dong, Seoul 121791, South Korea

[2] Soongsil Univ, Sch Elect Engn, Seoul 156743, South Korea

来源：

ANALYSIS AND DESIGN OF INTELLIGENT SYSTEMS USING SOFT COMPUTING TECHNIQUES | 2007年 / 41卷

关键词：

D O I：

10.1007/978-3-540-72432-2_19

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Fuzzy logic has been successfully used for nonlinear control systems. However, when the plant is complex or expert knowledge is not available, it is difficult to construct the rule bases of fuzzy systems. In this paper, we propose a new method of how to construct automatically the rule bases using fuzzy neural network. Whereas the conventional methods need the training data representing input-output relationship, the proposed algorithm utilizes the gradient of the performance index for the construction of fuzzy rules and the tuning of membership functions. Experimental results with the inverted pendulum show the superiority of the proposed method in comparison to the conventional fuzzy controller.

引用

页码：185 / +

页数：3

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